In [1]:
cd E:\karthi_m\wind

E:\karthi_m\wind
In [2]:
import pandas_profiling
In [3]:
import pandas as pd
In [4]:
da=pd.read_csv('data1.csv')
In [5]:
da.columns
Out[5]:
Index(['power', 'windspeed', 'airdensity', 'amb_temp', 'nac_direction',
       'blds_pitchangle', 'rtr_rpm', 'gen_rpm', 'wtg_state'],
      dtype='object')
In [8]:
da['wtg_state'].value_counts()
Out[8]:
ok                   44020
wind low              8658
curtailed             4187
Gen not conn          3896
high wind cut-out       29
Name: wtg_state, dtype: int64
In [9]:
da.head()
Out[9]:
power windspeed airdensity amb_temp nac_direction blds_pitchangle rtr_rpm gen_rpm wtg_state
0 964.5 9.1 1.162127 27 61.8 -3.0 14.1 1305.0 ok
1 1025.1 9.6 1.162127 27 61.8 -3.1 14.4 1336.0 ok
2 1179.7 9.6 1.162127 27 61.8 -2.9 14.4 1330.0 ok
3 1754.5 11.2 1.162127 27 65.2 -1.5 14.5 1345.0 ok
4 1826.8 11.4 1.162127 27 66.6 -1.3 14.5 1344.0 ok
In [10]:
pandas_profiling.ProfileReport(da)
Out[10]:




















In [12]:



     


profile = pandas_profiling.ProfileReport(da)
rejected_variables = profile.get_rejected_variables()



     


















    
    































In [ ]:



     


rejected_variables



     















In [ ]:



     


profile = pandas_profiling.ProfileReport(iris_data)
profile.to_file(outputfile="../profiling_iris.html")